Pattern formation and spatial solitons in bistable liquid-crystal microcavities

We report on spatial pattern formation, and appearances of 'optical bullet holes' in single-mode microcavities that are filled with liquid-crystals, when pumped above the cavity resonance frequency. These phenomena only occur beyond the bistability threshold. ©2002 Optical Society of America.

Spatial repeatability of dynamic tyre forces generated by heavy vehicles

Road damage due to heavy vehicles is thought to be dependent on the extent to which lorries in normal traffic apply peak forces to the same locations along the road. A validated vehicle simulation is used to simulate 37 leaf-sprung articulated vehicles with parametric variations typical of vehicles in one weight class in the highway vehicle fleet. The spatial distribution of tyre forces generated by each vehicle is compared with the distribution generated by a reference vehicle, and the conditions are established for which repeated heavy loading occurs at specific points along the road. It is estimated that approximately two-thirds of vehicles in this class (a large proportion of all heavy vehicles) may contribute to a repeated pattern of road loading. It is concluded that dynamic tyre forces are a significant factor influencing road damage, compared to other factors such as tyre configuration and axle spacing.

Investigation of spatial repeatability using a tire force measuring mat

A portable mat for measuring the dynamic tire forces of commercial vehicles is described. The mat is 56 m long and 13 mm thick and has 141 capacitative strip sensors spaced at 0.4-m intervals. The accuracy of the mat for measuring dynamic tire forces generated by heavy commercial vehicles is assessed using an instrumented vehicle. The spatial repeatability of dynamic wheel loads generated by 14 uninstrumented articulated vehicles is investigated, and it is concluded that approximately half of the vehicles tested are likely to contribute to a repeatable pattern of road loading.

Slowness and sparseness lead to place, head-direction, and spatial-view cells.

We present a model for the self-organized formation of place cells, head-direction cells, and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli. The model comprises a hierarchy of Slow Feature Analysis (SFA) nodes, which were recently shown to reproduce many properties of complex cells in the early visual system []. The system extracts a distributed grid-like representation of position and orientation, which is transcoded into a localized place-field, head-direction, or view representation, by sparse coding. The type of cells that develops depends solely on the relevant input statistics, i.e., the movement pattern of the simulated animal. The numerical simulations are complemented by a mathematical analysis that allows us to accurately predict the output of the top SFA layer.